This article discusses technology and opportunities available to embrace artificial intelligence (AI) in the design of autonomous wireless systems. A vision is presented for knowledge-driven wireless operation by means of AI disciplines, such as sensing, reasoning, knowledge management, and active learning. The aim is to provide readers with the motivation and a general big data-independent AI methodology for autonomous agents in the context of self-organization in real time by unifying knowledge management with sensing, reasoning, and active learning. Differences between training-based methods for matching problems and training-free methods for environment-specific problems are highlighted. Finally, we conceptually introduce the functions of an autonomous agent with knowledge management.
No takes yet. Share an insight, caveat, or question.
Haris Gacanin (2019) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: